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Computes the top-k singular triplets or eigenpairs of large sparse and structured matrices: the computation behind principal component analysis on big sparse data, spectral embeddings, and low-rank approximation. Every result carries a numerical certificate with residuals, a backward-error bound, orthogonality loss, and a pass/fail flag, and bounds that can only be estimated are reported as such rather than passed. Centered, scaled, and composed operators are solved through native 'C++' kernels without forming dense matrices. Drop-in replacements for the 'RSpectra' interface are included.
| Version: | 1.0.2 |
| Depends: | R (≥ 4.1) |
| Imports: | Matrix, methods |
| Suggests: | bench, knitr, rmarkdown, RSpectra, irlba, rsvd, testthat (≥ 3.0.0) |
| Published: | 2026-07-25 |
| DOI: | 10.32614/CRAN.package.eigencore |
| Author: | Bradley Buchsbaum [aut, cre, cph] |
| Maintainer: | Bradley Buchsbaum <brad.buchsbaum at gmail.com> |
| BugReports: | https://github.com/bbuchsbaum/eigencore/issues |
| License: | MIT + file LICENSE |
| URL: | https://bbuchsbaum.github.io/eigencore/, https://github.com/bbuchsbaum/eigencore |
| NeedsCompilation: | yes |
| SystemRequirements: | C++17 |
| Materials: | README, NEWS |
| CRAN checks: | eigencore results |
| Reference manual: | eigencore.html , eigencore.pdf |
| Vignettes: |
Benchmark smoke tests (source, R code) Certificates: reading the numerical evidence (source, R code) Get started with eigencore (source, R code) Generalized eigenvalue problems with eigencore (source, R code) |
| Package source: | eigencore_1.0.2.tar.gz |
| Windows binaries: | r-devel: eigencore_1.0.2.zip, r-release: eigencore_1.0.2.zip, r-oldrel: eigencore_1.0.2.zip |
| macOS binaries: | r-release (arm64): eigencore_1.0.2.tgz, r-oldrel (arm64): eigencore_1.0.2.tgz, r-release (x86_64): eigencore_1.0.2.tgz, r-oldrel (x86_64): eigencore_1.0.2.tgz |
| Old sources: | eigencore archive |
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